Comparison of Stimulus Types for Retinotopic Cortical Mapping of Macular Disease

Purpose Retinotopic maps acquired using functional magnetic resonance imaging (fMRI) provide a valuable adjunct in the assessment of macular function at the level of the visual cortex. The present study quantitatively assessed the performance of different visual stimulation approaches for mapping visual field coverage. Methods Twelve patients with geographic atrophy (GA) secondary to age-related macular degeneration (AMD) were examined using high-resolution ultra-high field fMRI (Siemens Magnetom 7T) and microperimetry (MP; Nidek MP-3). The population receptive field (pRF)-based coverage maps obtained with two different stimulus techniques (moving bars, and rotating wedges and expanding rings) were compared with the results of MP. Correspondence between MP and pRF mapping was quantified by calculating the simple matching coefficient (SMC). Results Stimulus choice is shown to bias the spatial distribution of pRF centers and eccentricity values with pRF sizes obtained from wedge/ring or bar stimulation showing systematic differences. Wedge/ring stimulation results show a higher number of pRF centers in foveal areas and strongly reduced pRF sizes compared to bar stimulation runs. A statistical comparison shows significantly higher pRF center numbers in the foveal 2.5 degrees region of the visual field for wedge/ring compared to bar stimuli. However, these differences do not significantly influence SMC values when compared to MP (bar <2.5 degrees: 0.88 ± 0.13; bar >2.5 degrees: 0.88 ± 0.11; wedge/ring <2.5 degrees: 0.89 ± 0.12 wedge/ring; >2.5 degrees: 0.86 ± 0.10) for the peripheral visual field. Conclusions Both visual stimulation designs examined can be applied successfully in patients with GA. Although the two designs show systematic differences in the distribution of pRF center locations, this variability has minimal impact on the SMC when compared to the MP outcome.


Introduction
Retinotopic mapping of the visual cortex based on functional magnetic resonance imaging (fMRI) acquired with blood oxygenation level-dependent (BOLD) contrast reveals the systematic representation of visual space in the visual cortex. 1 Retinotopic organization describes a feature of the visual system whereby every point on the retina corresponds to a specific point inside the visual cortex. The singleneuron response on the cortex to a visual stimulus is called a receptive field. It is not possible to measure activation at a single-neuron level due to limitations in fMRI resolution. The clustered activation within a three-dimensional measurement region corresponds to a population of neurons, referred to as a population-receptive field (pRF). Visual stimuli moving through the subject's field of view in a known manner excite specific patterns in the visual cortex and allow for the reconstruction of the retinotopic organization. 2,3 It is possible to determine these pRFs in vivo using the advanced computational neuroimaging approach of pRF mapping.
Previous studies have shown that pRF mapping provides objective functional data with high concordance to conventional testing, including microperimetry and optical imaging in both patients with central or peripheral retinal scotomata and healthy controls with artificial scotomata. 4,5 Other studies investigating retinal diseases [6][7][8][9] or retrochiasmal visual pathway lesions 10 have shown similar results. A combination of pRF mapping with conventional testing in patients with retinal dysfunction allows for a more objective assessment of visual function as bias from attention level changes is minimized, of particular importance for longitudinal studies aimed at assessing treatment effects in novel therapeutic interventions. This was recently shown in patients with RPE65-associated retinal dystrophy who, following gene replacement therapy, demonstrated widespread cortical activation in areas with an undetectable cortical response prior to treatment. 11 The standard setup for pRF mapping is based on visual stimuli resembling either rotating wedges and expanding/contracting rings as stimulus patterns 12,13 or bar apertures moving through the visual field in different directions, both revealing an isoluminant reversing checkerboard. 3 Although different variants of similar stimuli have been used, for example, landscapes, textures, animals, or faces, 14 either bar or wedge/ring stimuli remain the prime pRF mapping approaches. [15][16][17] Fundamental to any future clinical utility of pRF mapping is the assessment of whether the choice of visual stimulation patterns might bias pRF mapping results in patients suffering from retinal disease.
Geographic atrophy (GA), a common feature of macular disease, is characterized by sharply demarcated central macular atrophy and central visual field loss. Macular lesions may initially appear perifoveally and expand over a number of years to involve the fovea. 18 This distinct lesion pattern makes patients with GA prime subjects for exploring the cortical representation of central retinal scotomata. The method of pRF mapping is perfectly suited for the measurement of scotomata yielding very high reproducibility values, 19 even though biases in the modeling results are introduced. 20 The present study utilizes a crossover design to compare pRF maps obtained from wedge/ring stimu-lation to those from bar stimulation in patients with GA secondary to age-related macular degeneration (AMD).

Patients and Methods
Twelve patients with GA (8 men and 4 women; age = 72.6 ± 5.1 years) were recruited and underwent fMRI measurements. Written informed consent was obtained from all subjects before their participation. All patients had a secure clinical diagnosis supported by optical imaging studies. Inclusion criteria were a central, welldemarcated atrophic macular lesion; a central scotoma not exceeding 15 degrees visual angle diameter and fixation stability classified as stable or relatively unstable as measured by microperimetry. No patients with preferred retinal locus (PRL) were included. The study was approved by the local ethics committee.

Clinical Examination
Patients underwent a full ophthalmic examination, including slit-lamp examination and dilated fundus examination, fundus autofluorescence imaging, optical coherence tomography, and microperimetry. Best corrected visual acuity (BCVA) was measured using Early Treatment Diabetic Retinopathy Study (ETDRS) charts.

Retinal Imaging
Spectral-domain optical coherence tomography (SD-OCT) and blue-light fundus autofluorescence (FAF) images were recorded using a Spectralis HRA and OCT system (Heidelberg Engineering, Heidelberg, Germany) to evaluate retinal structure.

Microperimetry
Macular function was assessed by an MP-3 microperimeter (MP; Nidek, Padova, Italy). Stimulus intensity ranged from 0 dB to 32 dB in 1 dB steps, with the initial intensity at 17 dB. The stimulus pattern consisted of a foveal 3 × 3 grid surrounded by 3 rings at a radius of 3 degrees (8 points), 5.1 degrees (12 points), and 7 degrees (12 points) eccentricity. MP was measured at the anatomic fovea. Fixation stability was assessed as part of the microperimetric examination. Fixation was classified as stable when 90% of fixations were located within a 2 degrees circle, as relatively unstable when ≥80% of fixations were located within a 2 degrees circle and as unstable when less than 80% of fixations were located within a 2 degrees circle.

Functional MRI Measurements
Functional MRI measurements were performed using a 32-channel head coil in an ultra-high field Siemens MAGNETOM 7T scanner (Siemens Healthineers, Erlangen, Germany). Subjects participated in one scanning session including four functional runs, acquired using the CMRR EPI sequence 21 at an isotropic spatial resolution of 1 mm, matrix size = 128 × 128; TR/TE = 2000/25.2 ms; GRAPPA = 2; slice spacing = 10%. Every run included 32 slices covering the subject's visual cortex, placed perpendicular to the calcarine sulcus. Further, a structural full-brain image was obtained using a magnetization-prepared rapid gradient-echo (MPRAGE) sequence with 0.7 mm isotropic resolution. Each scanning session lasted approximately 1 hour.
Stimuli were presented via a back-projection screen mounted at the end of the patient's bed. Subjects viewed the screen through a mirror attached to the head coil with a mean distance between the eyes and the screen of 62 cm. If both eyes were affected by GA, the study eye was chosen randomly. One eye was patched to focus the measurement on eye-specific pathology. Subject motion was restricted by extensive padding.
Preprocessing of the functional data was performed in a custom-built pipeline (Matlab, SPM, and FSL) including slice-timing correction, re-alignment, distortion correction, and spatial smoothing using a Gaussian kernel with FWHM of 2 mm. The anatomic image was segmented using Freesurfer (https://surfer.nmr.mgh.harvard.edu) to obtain white and grey matter masks and manually corrected for segmentation and topological errors.
The two measured runs per session were averaged before analysis to improve the signal-to-noise ratio. The pRF analysis was performed using the Matlabbased toolbox mrVista (https://github.com/vistalab/ vistasoft). Within this analysis, time-course models are created based on different positions on the visual field (x and y) and receptive field sizes. For every voxel inside the participant's visual cortex, the best-fitting model is determined and a discrete mapping between the position on the visual field and the cortex is established. All pRF analyses were performed without any information on the scotoma status of the subjects studied. All reported data are thresholded at 20% variance explained.

Stimuli
Stimulation patterns during the fMRI examination covered the central 14 degrees visual angle and were presented using mrVista (Vista Lab, Stanford University, Stanford, CA) within the Matlab programming environment (The MathWorks, Inc., Natick, MA). Two stimulus designs, "bar" and "wedge/ring," were examined (see Fig. 1).
The first stimulus consisted of a bar moving across an isoluminant screen while exposing a checkerboard pattern reversing with a frequency of 8 Hz. Bar width was 1.75 degrees, corresponding to 12.5% of the total stimulus coverage, and crossed the screen in 18 discrete  steps, each separated by 0.8 degrees visual angle in space and TR = 2 seconds in time. The bar moved across the screen in eight different directions for each run. After each crossing, the bar was rotated by 45 degrees. With pauses of 12 seconds duration after each diagonal pass, during which the subject was presented a blank grey screen of similar mean luminance, a singlerun length was 5 minutes 36 seconds or 168 volumes. Run length was identical for both stimulus variants.
The second stimulus consisted of a counterclockwise rotating wedge, with a width of 45 degrees and a step size of 20 degrees, performing two full rotations in 36 steps and a ring with a thickness of 0.875 degrees visual angle, expanding from the center twice in 36 steps (step size 0.43 degrees). This whole sequence was repeated in opposite directions (i.e. clockwise rotating wedge and contracting ring). Between each wedge or ring period, the grey background image was shown for 12 seconds as a baseline. The exposed checkerboard is radially symmetrical.
Patients were instructed to fixate on a small dot (12 pixels or 0.22 degrees visual angle diameter) in the center of the screen. As good fixation is essential, thin diagonal lines (5 pixels or 0.09 degrees visual angle diameter) crossing at the center dot were also displayed to assist patients to maintain stable fixation. The color of the fixation dot and cross was changed pseudo-randomly, and subjects were asked to report color changes via a button press. This measure was used to assess subject compliance.

Correlation of Visual Field Coverage and Microperimetry
Coverage maps were created by plotting the maximum surface of all above-threshold pRFs resulting in a map of the visual field ranging between 0 and 1. Following the study by Ritter et al., 4 pRF coverage values above a threshold of 0.7 were classified as areas with good vision and everything below as scotomata.
For comparison, MP results were binarized such that all measurement points with values higher than 0 were classified as areas with vision, whereas 0 was classified as scotomatous. The most peripheral ring of the MP measurement points was not taken into consideration as it fell outside of the area stimulated during the fMRI measurements.
MP and pRF maps were compared on a subjectby-subject basis based on the binarized coverages. The simple matching coefficient (SMC) was used to compare both maps quantitatively within the range between 0 (all point values differ) and 1 (all point values are identical).

SMC = # matching points # points
In addition to the full field of view, SMC was calculated also for areas with low eccentricity (<2.5 degrees) and high eccentricity (>2.5 degrees). 22 Both maps and the SMC appear in Figure 2.

Statistical Comparison
To investigate possible systematic biases in pRF parameters between the two stimulus variants, we calculated differences in eccentricity, polar angle, pRF size, and variance explained per subject. These differences were averaged per subject and submitted to onesample t-tests to test for stimulus-specific differences across subjects.

Results
The clinical characteristics of the patient cohort are summarized in Tables 1 and 2. Three of the 12 patients with GA failed to meet data quality criteria due to poor performance during the fMRI runs (reporting changes in fixation dot color or excessive movement) or MP fixation stability. For all patients, pRF analyses yielded the expected patterns of eccentricity, polar angle, and pRF sizes. Figure 2 shows a comparison of the data derived from FAF, MP, and pRF mapping for all patients.  Although the paracentral scotoma is clearly delineated in the distribution of pRF centers on visual field maps, it is not visible in the binarized pRF maps. In the pRF map based on wedge/ring stimuli, the central clustering of pRF centers introduces supposed peripheral visual field defects. There is a clear difference in the distribution of pRF centers between stimuli; pRF centers are distributed homogenously throughout the visual field in visual field maps derived from bar stimuli, but in visual field maps derived from wedge/ring stimuli, they are clustered toward the center (bar: <2. Close inspection of the data show differences between pRF maps created from wedge/ring and bar stimulus fMRI runs. Above-threshold pRF centers are generally located more toward the center of the visual field with wedge/ring stimuli than with bar stimuli. Figures 3, 4, and 5 show data from three patients with GA. Each figure includes MP results superimposed on fundus photographs, pRF coverage maps calculated from fMRI data with bar and wedge/ring stimuli as well as binarized MP, and binarized pRF coverage maps with bar and wedge/ring stimuli. In addition, the pRF-based eccentricity map of the patient is presented overlaid on the white matter/grey matter (WM/GM) surface mesh.

Quantitative Comparison
In a previous study, it was shown that wedge/ring compared to bar stimuli show improved fit in foveal areas up to about 2.5 degrees eccentricity. 22 After binarizing the visual field maps and splitting them according to this 2.5 degrees boundary, SMCs can be compared not only between the stimuli but also between central and peripheral parts of the visual field. SMC values for the bar stimulus reached a mean value of 0.88 ± 0.13 for central areas and 0.88 ± 0.11 for peripheral areas, wedge/wing stimuli had a mean SMC value of 0.89 ± 0.12 in central areas and a mean SMC of 0.86 ± 0.10 for the peripheral visual field. Details appear in Figure 1.
The Wilcoxon signed rank was calculated across all subjects comparing SMC values for bar and wedge/ring stimuli for both the whole visual field as well as for inner (<2.5 degrees) and outer (>2.5 degrees) areas. There were no significant differences between SMC values for full visual field (P = 0.598) nor inner and outer subdivisions (<2.5 degrees: P = 0.317; >2.5 degrees: P = 0.786). Spearman rank-order correlation coefficient between the binarized coverage map values of pRF results from bar and wedge/ring stimuli showed a significant correlation (r = 0.499, P = < 0.05).
The distribution of pRF centers between inner and outer parts of the visual field was also expressed as a percentage of the total. On average, bar stimulus results had 40% of pRF centers located in the inner 2.5 degrees visual angle averaged over all patients compared to 53% when using wedge/ring stimuli. The difference was statistically significant (P = 0.012, paired t-test).
This difference in distributions of pRF center positions between bar and wedge/ring stimuli was further examined based on eccentricity, polar angle, pRF size parameters, and variance explained values. The plots for these parameters including all patients' Figure 6. Point density plots comparing wedge/ring and bar results for eccentricity, polar angle, pRF size (sigma), and variance explained across all patients. Isodensity lines (grey, 20% steps) obtained from the initial point cloud and identity lines (red) are also shown.
V1 data points are displayed in Figure 6. Bar and wedge/ring values are plotted along the x-and yaxis, respectively. Due to the high number of points, initial point clouds were converted to histograms. In addition, isodensity lines (grey) obtained from the initial point cloud are presented. Points plotted on the 45 degrees line (red) indicate identical results in both analyses.
Most eccentricity values fall below the red identity line, indicating lower eccentricity results using the wedge/ring stimulus (t(8) = 2.676, P = 0.028). In contrast, polar angles closely follow the red identity line, showing high similarity across both stimuli (t(8) = −0.226, P = 0.827). The third pRF parameter examined is size (sigma). Here, the discrepancy between pRF size parameters obtained from bar or wedge/ring stimulation is considerable. Most pRF size values fall below the red identity line demonstrating a clear, systemic bias of the wedge/ring stimulus towards smaller pRF size estimates when compared to bar stimuli (t(8) = 5.271, P = 0.001). Variance explained values show mostly similar results for the two stimuli, with a trend toward higher values in wedge/ring stimulation (t(8) = −1.878, P = 0.097). Relation of pRF size in regard to eccentricity can be seen in Figure 7; pRF sizes are stable within the central 4 degrees radius for both stimuli, however, showing higher values for the bar stimulus throughout the entire field of view. For the wedge/ring stimulus, the pRF size is strongly increased for the peripheral field of view.

Discussion
The present study examines whether the choice of either bar or wedge/ring stimuli for pRF mapping in patients with GA secondary to AMD shows differences in distribution, position, or visual field coverage of pRF centers. All data were acquired using ultra-highfield MRI for maximum spatial resolution and sensitivity. Overall, analyses of pRF data for both stimuli show expected pRF size, eccentricity, and polar angle. The localized central macular dysfunction in the GA area with peripheral sparing was revealed by both stimuli at the cortical level, thereby complementing MP and retinal imaging (FAF and OCT).
Group-averaged SMC in patients with GA based on 7 Tesla fMRI data varied from 0.86 to 0.89 and corroborate previously published results where conventional test results, including MP and structural imaging, were linked to 3T fMRI based pRF-mapping of V1 in patients with Stargardt disease or retinitis pigmentosa. 4 We utilized a similar methodology binarizing the coverage maps gained from MP and pRF mapping. This binarization is required as pRF mapping, in contrast to MP, uses only a single stimulus intensity and regions exhibiting low pRF coverage are therefore not equivalent to MP test points with low dB values. Coverage maps were also compared on a subject-by-subject basis and showed a high agreement. Although a number of studies have reported comparisons among retinal findings, visual fields, and fMRI results in a variety of visual pathway disorders, such as AMD, glaucoma or RP, [23][24][25] this study is the first to compare different stimulus modalities in the evaluation of retinotopic features in patients with localized macular abnormalities.
Artificial scotomata were used in a previous study 5 to simulate an unrealistically regular pattern of visual loss; artificial foveal scotomata with fixed location and size and sharp edges. This allowed for ground-truth conditions for exactly describing the effective retinal input generating the fMRI responses. Additionally, we showed that the presence of a central scotoma, even though it is a major disturbance in the model, does not negatively influence the pRF mapping results. In a different study, the influence of the stimulation paradigm on pRF results in healthy subjects showed systematic a bias toward more foveal pRF centers and lower pRF sizes using the wedge/ring stimulus. 22 The findings further indicated that wedge/ring stimuli might be preferable in studies targeting the central visual field up to 2.5 degrees eccentricity, whereas bar stimuli could be advantageous in regions peripheral to that border. Herein, both approaches are used and applied to a real-world clinical setting with patients with GA having real patterns of visual loss, including scotomata of different sizes with irregular borders. Similar systematic biases were observed when comparing the stimuli, which confirms pRF mapping to be a robust and reliable method.
SMC calculation revealed no significant differences between stimulus variants, confirming pRF to be a robust approach for visual field mapping. Visual inspection of historical data from healthy subjects suggested a central clustering of pRF centers when using wedge/ring stimuli but a more homogenous distribution when using bar stimuli. This was confirmed by analysis of the percentage of pRF centers showing a statistically significant difference between stimulus variants in the distribution of pRF centers in inner and outer parts of the visual field. Further examination of pRF parameters revealed a bias of wedge/ring stimulus results toward lower eccentricity values. The size of pRFs shows a much stronger bias of the wedge/ring stimulus results toward markedly smaller pRF size estimates compared to bar stimulus results. In contrast, polar angles show high similarity across both stimuli. Table 3 shows that the variance explained threshold does exclude a slightly higher number of voxels with the bar compared to the wedge/ring stimulus, however, no significant difference was found. One explanation for the marked differences in pRF sizes between both stimulus variants might lie in the coverage of the bar stimulus compared to the wedge/ring stimulus. For the central visual field, only small areas are stimulated by the wedge/ring stimulus allowing for simultaneous viewing. This allows for mapping very small pRF sizes in foveal areas, whereas the bar stimulus has a continuous thickness throughout the whole visual field, possibly penalizing smaller pRFs. A Areas are subdivided into 0 to 2.5 degrees and 2.5 to 7 degrees based on the variance explained changing with increasing eccentricity based on a previous study.
further confounding factor is the difference of spatial characteristics of the checkerboard patterns. Although the bar stimulus exposes a rectangular checkerboard, wedge/ring stimuli expose radially symmetric checkerboards with a changing patch size with eccentricity. Previous publications try to adapt the stimulus regarding this problem by introducing eccentricity-scaled bar stimuli, 26 however, these designs do not allow for a homogenous sampling of the visual field, which is of vast importance when examining patients with visual field loss.
The pRF sizes are stable within the central 4 degrees radius for both stimuli (see Fig. 7), however, showing higher values for the bar stimulus throughout the entire field of view. For the wedge/ring stimulus, the pRF size is strongly increased for the peripheral field of view, replicating previous findings in healthy subjects. 22 There is one difference though: the steep slope toward the central visual field is missing. This could be explained by the fact that the measured scotomata are not taken into account in the model, leading to an increase in pRF sizes for central within scotoma pRFs. 20 Data from individual patients showed stimulusdependent differences between the binarized pRF maps. For example, the lower SMC value of bar stimuli maps of patient 5 indicates both the missing central scotoma (due to the slight misalignment of the scotoma in MP and the pRF map) and the immediately adjacent supposedly mistaken visual field defect (a consequence of the misalignment).
It has been shown that fMRI based pRF mapping is a highly stable method in healthy subjects 27 and in subjects with simulated scotoma, 22 in terms of pRF center position, and although we confirmed the stabil-ity when calculating SMC similarity of the two stimuli, there are significant differences in regard to pRF center distribution. At the same threshold of variance explained, wedge/ring stimuli show proportionately more above-threshold voxels in the central visual field. This distribution difference compared to bar results may arise from the changing size of the wedge/ring stimulus throughout the visual field (i.e. thickness changes from foveal to peripheral areas). This is likely to relate to the high cortical magnification factors of central regions and smaller pRF sizes. 28 Subsequently, with changing pRF sizes in relation to eccentricity, larger parts of the peripheral visual field are exposed to wedge/ring stimuli compared with bar stimuli leading to less distinct stimulation and thus lower variance explained in voxels located in these areas. 22 Size parameters have shown lower reproducibility in the literature, which might be explained by their strong dependency on the hemodynamic response function used for the analyses. 29 The data from three initially recruited and scanned patients were excluded because of poor compliance in the MRI scanner (2 patients) or unstable fixation during the MP (1 patient). Both patients excluded for pRF instability demonstrated relatively unstable fixation on MP, suggesting fixation stability to be a major limiting factor in pRF mapping based on fMRI and that poor fixation greatly reduces the quality of pRF mapping results (see Table 3). The absence of eye-tracking at the 7 Tesla MRI scanner is a recognized limitation of the current study. A further limitation relates to the small field of view of the selected fMRI stimulus, due to the comparatively small bore of the 7T MRI scanner. Although the data contribute toward best practice methods in the use of fMRI in the assessment of patients with macular disease, the small sample size limits the ability to extrapolate to a larger patient population. Furthermore, due to the fact that no ground truth is known regarding pRF size, we cannot give a profound assessment of whether pRF sizes obtained using bar or wedge/ring stimuli are more neurophysiologically correct.
A major potential use for pRF mapping could be in the evaluation of patients receiving novel gene or cell replacement therapies, where functional gain of previously nonfunctional areas could be demonstrated objectively at the level of the visual cortex, as suggested by the recent data from patients with Leber congenital amaurosis (LCA). 11 This method could provide additional quantitative biomarkers to serve as outcome measures augmenting existing clinical evaluations in novel treatment interventions.
One possible solution to compensate for the stimulus-specific coverage map differences would be a combination of multiple stimuli. Data have shown 22 that the combination of pRF mapping data unsurprisingly improves the homogeneity of coverage map results. Combining multiple runs further effectively compensates the stimulus-specific deficits (i.e. pRF center distribution) in visual field coverage. It may also be of interest in future studies to concentrate upon the distribution of pRF centers as opposed to pRF size when interpreting visual field maps. A perfect example for this phenomenon would be the maps of patient 3 where the scotoma is demarcated in great detail irrespective of the stimulus used but occluded by pRF size on visual field maps.

Conclusions
The present study further confirms pRF mapping to be a robust and reliable method and demonstrates that while bar and wedge/ring stimuli may show significant differences in the distribution of pRF centers across the visual field, this variability has minimal impact on the comparison with microperimetry. The demonstrated differences in pRF mapping results consequent upon the choice of visual stimulus needs adequate consideration if pRF mapping is to be used in a clinical setting. The selection of the most appropriate visual stimulus for assessment of visual cortical function in retinal disease needs to be based upon established stimulus-specific relationships between dysfunction in defined retinal regions and activity in the corresponding cortical areas. Future studies that focus on comparison measures beyond the SMC may further ascertain and quantify the characteristics of individual stimulus modalities.